Parallel and converging multisensory cascades in the Drosophila connectome

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 8, 2024

Connectomes are network maps of synaptic connectivity. A key functional role any connectome is to constrain inter-neuronal signaling and sculpt the flow activity across nervous system. therefore play a central in rapid tranmission information about an organism’s environment from sensory neurons higher-order for action planning ultimately effectors. Here, we use parsimonious model spread investigate connectome’s shaping putative cascades. Our allows us simulate pathways sensors rest brain, mapping similarity these between different modalities identifying convergence zones–neurons that activated simultaneously by modalities. Further, considered two multisensory integration scenarios – cooperative case where interacted “speed up” (reduce) neurons’ activation times competitive “winner take all” case, streams vied same neural territory. Finally, data-driven algorithm partition into classes based on their behavior during cascade simulations. work helps underscore “simple” models enriching data, while offering classification joint connectional/dynamical properties.

Language: Английский

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From connectome to effectome: learning the causal interaction map of the fly brain

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2023, Volume and Issue: unknown

Published: Nov. 3, 2023

A long-standing goal of neuroscience is to obtain a causal model the nervous system. This would allow neuroscientists explain animal behavior in terms dynamic interactions between neurons. The recently reported whole-brain fly connectome [1-7] specifies synaptic paths by which neurons can affect each other but not whether, or how, they do vivo. To overcome this limitation, we introduce novel combined experimental and statistical strategy for efficiently learning brain, refer as "effectome". Specifically, propose an estimator dynamical systems brain that uses stochastic optogenetic perturbation data accurately estimate effects prior drastically improve estimation efficiency. We then analyze circuits have greatest total effect on dynamics discover that, fortunately, dominant significantly involve only relatively small populations neurons-thus imaging, stimulation, neuronal identification are feasible. Intriguingly, find approach also re-discovers known generates testable hypotheses about their dynamics. Overall, our analyses provide evidence global generated large collection often anatomically localized operating, largely, independently other. turn implies principal neuroscience, be feasibly obtained fly.

Language: Английский

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The Oviposition Inhibitory Neuron is a potential hub of multi-circuit integration in the Drosophila brain

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 26, 2024

Abstract Understanding how neural circuits integrate sensory and state information to support context-dependent behavior is a central issue in neuroscience. In Drosophila, oviposition complex process which the fly integrates context choose an optimal location lay her eggs. The circuit that controls sequence known, but multiple modalities internal states not. We investigated circuitry underlying high-level processing related using Hemibrain connectome. identified Oviposition Inhibitory Neuron (oviIN) as key hub analyzed its inputs uncover potential parallel pathways may be responsible for computations decision-making. applied graph-theoretic analyses on sub-connectome of oviIN identify modules neurons constitute novel circuits. Our findings indicate form from unstructured neuropils Superior Protocerebrum where have been known occur.

Language: Английский

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Can bacteria think?

EMBO Reports, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 25, 2024

Language: Английский

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Inferring community architectures of multisensory pathways inDrosophilavia unsupervised network embedding

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 22, 2024

Abstract Understanding the complex architecture and functions of neural circuits is central to unraveling mechanisms multisensory integration. In this study, we analyzed structural properties Drosophila adult brain infer community structures within pathways. We adopt a network embedding method developed by ourselves, Bidirectional Heterogeneous Graph Neural Network with Random Teleport (BHGNN-RT), designed generate vector representations neurons in directed, heterogeneous connectome. This approach takes advantage both connectivity heterogeneity features, enabling effective clustering revealing hierarchical architectures olfactory broader systems. applied BHGNN-RT fly connectome examine connectivity-based organization major neuronal classes along pathways, distinct groups unique patterns antennal lobe, lateral horn, mushroom body, other regions. Further analysis showed how different contribute integration sensory information also investigated bilateral symmetry pathway, shedding light on signals are processed ipsilateral contralateral connections ensure robust perception. Our findings demonstrate utility graph representation learning analyzing The insights gained from provide deeper understanding comprehension underlying

Language: Английский

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